Indeed, we found that mice chronically, but not acutely, infected with T. gondii exhibited a significant expansion and activation of type 1 and type 2 conventional dendritic cells (cDC) in the dural meninges. cDC1s and cDC2s were both capable of sampling cerebrospinal fluid (CSF)-derived protein and were found to harbor processed CSF-derived protein in the draining deep cervical lymph nodes. Disrupting meningeal lymphatic drainage via ligation surgery led to a reduction in CD103+ cDC1 and cDC2 number in the deep cervical lymph nodes and caused an impairment in cDC1 and cDC2 maturation. Concomitantly, lymphatic vessel ligation impaired CD4+ and CD8+ T cell activation, proliferation, and IFN-γ production at this site. Surprisingly, however, parasite-specific T cell responses in the brain remained intact following ligation, which may be due to concurrent activation of T cells at non-CNS-draining sites during chronic infection. Collectively, our work reveals that CNS lymphatic drainage supports the development of peripheral T cell responses against T. gondii but remains dispensable for immune protection of the brain.The discovery of meningeal lymphatic vessels that drain the CNS has prompted new insights into how immune responses develop in the brain. In this study, we examined how T cell responses against CNS-derived antigen develop in the context of infection. We found that meningeal lymphatic drainage promotes CD4 Toxoplasma gondii, an intracellular protozoan parasite that causes chronic, lifelong infection in a wide range of mammalian hosts, including humans  subsets in response to brain infection, we performed spectral flow cytometry on cells purified from the dural meninges of naïve, acutely infected (2 weeks post-infection), or chronically infected (6 weeks post-infection) C57BL/6 mice (T. gondii (T. gondii infection remains unresolved. While there was no difference in the number of cDC1s (CD45+Lin-CD11chiMHC IIhiCD64-CD26+XCR1+SIRPα-) or cDC2s (CD45+Lin-CD11chiMHC IIhiCD64-CD26+XCR1-SIRPα+) in naive and acutely infected mice, by 6 weeks post-infection (wpi) there was a threefold increase in the number of cDC1s and sixfold increase in the number of cDC2s in the dural meninges  . Even beter 5 hr . By contter 5 hr . Furthernjection , the latnjection .T. gondii, activated (CD44hiCD62Llo) CD4+ and CD8+ T cell number in the ILNs was greatest during acute infection (2 wpi) , when very few parasite-specific T cells were detectable in the DCLNs  , consistat 2 wpi . Expansi 6–8 wpi . To bettvalbumin . Consistnfection , the peahe DCLNs . By contnd 6 wpi . These rnd 6 wpi , whereasnd 6 wpi . NotablyT. gondii infection  confirmed the efficacy of the procedure and demonstrated a greater than 95% reduction in outflow of CSF-derived components to the DCLNs in ligated animals . Remarkably, IFN-γ production was reduced by 69% among CD4+ T cells and 60% among CD8+ T cells after ligation surgery  cells did not change   in addithe brain .T. gondii. These results contrast with recent studies showing that T cell responses against brain tumors and host protection against acute viral infection of the brain are supported by meningeal lymphatic drainage to the deep cervical lymph nodes  to C57BL/6 mice 5–6 weeks after infection with either Pru-OVA or parental strain Pru . We then+ T cells in CNS-draining lymph nodes is predominantly antigen-dependent, and only a limited degree of proliferation can be attributed to bystander activation. The OT-I cells used for adoptive transfer also expressed GFP under the control of the Nr4a1 (Nur77) promoter, a reporter system that was originally developed as a tool to track antigen-dependent TCR stimulation , C57BL/6-Tg(TcraTcrb)1100Mjb/J , and C57BL/6-Tg(Nr4a1-EGFP/cre)820Khog/J  strains were originally purchased from the Jackson Laboratory and then maintained within our animal facility. B6.SJL-aPepcbPtprc/BoyCrCrl  and Swiss Webster (#024) strains were purchased from Charles River Laboratories. To generate OT-I (CD45.1 congenic) mice, OT-I and CD45.1 congenic strains were cross-bred within our facility. OT-I (CD45.1 congenic) mice were then crossed to GFPNr4a1 mice to generate OT-I/GFPNr4a1 (CD45.1 congenic) mice for use in adoptive transfer studies. For experiments reported in this study, age-matched young adult female mice (7–10 weeks of age) were used. All experiments were approved by the Institutional Animal Care and Use Committee at the University of Virginia under protocol number 3968.All mice were housed at University of Virginia specific pathogen-free facilities with a 12 hr light/dark cycle. C57BL/6 J (#000664), CBA/J (#000656), B6.Cg-Tg(Itgax-Venus)1Mnz/J  Swiss Webster mice and passaged through CBA/J mice. For experimental infections with the ME49 strain, tissue cysts were prepared from homogenized brains of chronically infected (4–8 weeks) CBA/J mice. Mice were then inoculated intraperitoneally (i.p.) with 10 tissue cysts of ME49 in 200 μl of 1 X PBS. The transgenic Prugniaud strain of T. gondii expressing ovalbumin (aa 140–386) and TdTomato (Pru-OVA) were generously provided by Anita Koshy (University of Arizona) and maintained by serial passage through human foreskin fibroblast (HFF) monolayers in parasite culture medium . The parental Prugniaud strain  was similarly maintained. For experimental infections with the Pru-OVA or parental Pru strains, tachyzoites were purified from HFF cultures by needle-passaging scraped cells and filtering the parasites through a 5.0 μm filter (EMD Millipore). Mice were then inoculated i.p. with 1000 tachyzoites of Pru-OVA or parental Pru in 200 μl of 1 X PBS.Mice were infected with avirulent, type II strains of T. gondii genome was performed as described previously  and CFX384 Real-Time System (Bio-Rad) to assay 500 ng of DNA per sample. A standard curve generated from 10-fold serial dilutions of T. gondii gDNA, isolated from cultured HFFs and ranging from 3 to 300,000 genome copies, was used to determine the total number of T. gondii genome copies per μg gDNA per tissue. For assessment of parasite burden by cyst counts, whole brains were minced with a razor blade and passed through an 18-gauge and 22-gauge needle to mechanically homogenize the tissue. A total of 30 μl of tissue homogenate was then mounted on a microscope slide and T. gondii cysts were enumerated using a DM 2000 LED brightfield microscope (Leica).For assessment of parasite burden by real-time PCR, genomic DNA (gDNA) was isolated from mouse brains, dural meninges, quadriceps femoris skeletal muscle, lymph nodes, or subcutaneous adipose tissue using the Isolate II Genomic DNA Kit  following the manufacturer’s instructions. Prior to tissue lysis, whole brains and skeletal muscle required mechanical homogenization using an Omni TH tissue homogenizer . Amplification of the 529 bp repeat element in the eviously , using tMice were anesthetized by i.p. injection of a solution containing ketamine (100 mg/kg) and xylazine (10 mg/kg) diluted in saline. Mice were secured in a stereotaxic frame with the head angled slightly downward. An incision in the skin was made at the base of the skull and the muscle layers overlying the atlanto-occipital membrane were retracted. A 33-gauge Hamilton syringe (#80308) was inserted at a steep angle through the membrane to inject the desired solution into the CSF-filled cisterna magna. After injection, the skin was closed using 5–0 nylon sutures and mice received a subcutaneous (s.c.) injection of ketoprofen (2 mg/kg). Mice were then allowed to recover on a heating pad until awake.Collecting lymphatic vessels afferent to the deep cervical lymph nodes were surgically ligated as previously described . Mice weTo assess the function of meningeal lymphatic drainage in mice that had received ligation surgery, tracers were injected into the cerebrospinal fluid (CSF) and outflow to the deep cervical lymph nodes or superficial cervical lymph nodes was measured. For qualitative assessment, 5 μl of 10% Evans blue (Sigma-Aldrich) diluted in artificial CSF  was introduced into the subarachnoid space of ligated or sham-operated mice by intra-cisterna magna (i.c.m.) injection. One hour after injection, mice were sacrificed and drainage of the dye to the DCLNs was visualized under a S6D stereomicroscope (Leica). For quantitative assessment, 3 μl of Alexa Fluor 594-conjugated ovalbumin  or Alexa Fluor 488-conjugated ovalbumin  diluted in aCSF (2 mg/ml) was introduced into the subarachnoid space of ligated or sham-operated mice by i.c.m. injection. Two hours after injection, mice were sacrificed and the amount of OVA-AF594 or OVA-AF488 present in the DCLNs or SCLNs was determined by fluorescence spectroscopy. Briefly, DCLNs and SCLNs were harvested and enzymatically digested with Collagenase D  at 37 °C for 30 min, followed by a 2 hr treatment in T-PER Tissue Protein Extraction Reagent (Thermo Scientific) at 4 °C. Samples were centrifuged at >10,000 rpm to remove cellular debris and the supernatant containing extracted protein was transferred to a black flat-bottom microwell plate . Relative fluorescence intensity of each sample was measured on a SpectraMax iD3 microplate reader (Molecular Devices) using an excitation wavelength of 590 nm and emission wavelength of 630 nm for OVA-AF594 and an excitation wavelength of 490 nm and emission wavelength of 530 nm for OVA-AF488 before comparison to a standard curve to determine the total amount of tracer that drained.The uptake and processing of CSF-derived protein by antigen-presenting cells outside the CNS was evaluated by injecting 3 μl of DQ-OVA  into the CSF of chronically infected C57BL/6 mice by i.c.m. injection. The fluorescent signal of proteolytically cleaved DQ-OVA, with a peak excitation wavelength of 505 nm and peak emission wavelength of 515 nm, was then detected by flow cytometry or confocal microscopy. For flow cytometry studies, the dural meninges, deep cervical lymph nodes, and inguinal lymph nodes were harvested and prepared as single-cell suspensions for cell surface staining 2 hr, 5 hr, or 24 hr after i.c.m. injection of DQ-OVA. For flow acquisition, fluorescence emitted by processed DQ-OVA was detected using the FL1 sensor (525/40 nm) of a Gallios flow cytometer (Beckman Coulter) or using a Cytek Aurora Flow Cytometry System. For imaging studies, mice were sacrificed 12 h after injection of DQ-OVA, and whole-mount dural meninges were fixed, then immunostained using directly-conjugated antibodies targeting MHC class II  and LYVE1 . Fluorescence emitted by processed DQ-OVA was detected using 488 nm laser excitation on a TCS SP8 confocal microscope (Leica).Image analysis was performed on dural meninges whole mounts or on sectioned brain tissue. After sacrifice, transcardiac perfusion of mice was performed using 20 ml of cold 1 X PBS. The dorsal aspect of the skull was removed and the dural meninges were fixed, while still attached to the skull bone, in 4% PFA for 6–8 hr at 4 °C. Then, as previously described , whole-m2+ or Mg2+, Gibco) with Collagenase D  and Collagenase VIII  at 37 °C for 30 min, before being passed through a 70 μm strainer (Corning). Cells were then pelleted, resuspended, and kept on ice. Deep cervical lymph nodes (DCLNs), which are positioned laterally to the trachea and underneath the sternocleidomastoid muscles, and inguinal lymph nodes (ILNs) were harvested bilaterally into cold complete RPMI media . Lymph nodes were mechanically homogenized and gently pressed through a 70 μm strainer (Corning). Cells were then pelleted, resuspended, and kept on ice. Brains were harvested into cold cRPMI, minced with a razor blade, and passed through an 18-gauge and 22-gauge needle for mechanical homogenization. Tissue was then digested in a solution containing collagenase/dispase  and DNase  at 37 °C for 45–60 min, before being passed through a 70 μm strainer (Corning) and washed with cRPMI. Myelin was separated from mononuclear cells by resuspending samples in 20 ml of 40% Percoll (Cytiva) and centrifuging at 650 g for 25 min. Myelin was aspirated and cell pellets were washed, resuspended, and kept on ice. Spleens were harvested into cold cRPMI, then mechanically homogenized and washed through a 40 μm strainer (Corning). Cells were resuspended in RBC lysis solution (0.16 M NH4Cl) for 2 min. Cells were then washed, resuspended, and kept on ice.After sacrifice, transcardiac perfusion of mice was performed using 20 ml of cold 1 X PBS. For analysis of the dural meninges, the dorsal aspect of the skull was removed and the dural meninges were carefully dissected from the skull bone under a S6D stereomicroscope (Leica). The tissue was then digested in 1 X HBSS (without CaMice were anesthetized by i.p. injection of a solution containing ketamine (100 mg/kg) and xylazine (10 mg/kg) diluted in saline. An incision in the skin was made at the base of the skull and the muscle layers overlying the atlanto-occipital membrane were retracted. A pulled glass capillary  was inserted through the membrane into the cisterna magna and 5–10 μl of CSF was collected per mouse. CSF from four to five mice was pooled, and a total of 25 μl of CSF per pooled sample was analyzed by flow cytometry.+ T cells were analyzed, cells were pre-incubated with PE-conjugated H-2Kb/OVA (SIINFEKL) tetramer (NIH Tetramer Core Facility) for 15 min at room temperature prior to cell surface staining. After surface staining, cells were washed with FACS buffer (0.2% BSA and 2 mM EDTA in 1 X PBS) and, if intracellular staining was performed, cells were treated with a fixation/permeabilization solution  overnight then stained for intracellular markers in permeabilization buffer  for 30 min at 4 °C. Finally, samples were resuspended in FACS buffer and acquired. Fourteen-color experiments were performed using a Cytek Aurora Flow Cytometry System  and prepared as follows: Cells were stained with a Live/Dead Fixable Red Dead Cell Stain  according to the manufacturer’s instructions. Cells were washed and then treated with 50 μl of Fc block (as above) for 10 min at room temperature. Cells were then stained for surface markers for 30 min at 4 °C. In experiments where SIINFEKL-specific CD8+ T cells were analyzed, cells were pre-incubated with PE-conjugated H-2Kb/OVA (SIINFEKL) tetramer (NIH Tetramer Core Facility) for 15 min at room temperature prior to cell surface staining. Finally, samples were resuspended in FACS buffer and acquired after spectral unmixing using single-color controls. Samples acquired on the Gallios flow cytometer and Cytek Aurora Flow Cytometry System were analyzed using FlowJo software v.10. For cerebrospinal fluid, cell counts were determined using absolute counting beads  pipetted into samples just prior to acquisition. For lymph nodes, brain, and dural meninges, cell counts were measured using a Hausser Scientific hemacytometer (Fisher Scientific). For samples analyzed using the Gallios flow cytometer, cells were stained for surface markers using the following eBioscience antibodies at 1:200 dilution: CD45-FITC (11-0451-82), CD62L-FITC (11-0621-85), CD80-FITC (11-0801-82), MHC class II (I-A/I-E)-PE (12-5321-82), CD69-PE (12-0691-82), CD11c-PerCP-Cy5.5 (45-0114-82), CD4-PerCP-Cy5.5 (45-0042-82), CD45-PerCP-Cy5.5 (45-0451-82), CD11b-PerCP-Cy5.5 (45-0112-82), CD8α-PerCP-Cy5.5 (45-0081-82), CD45.1-PerCP-Cy5.5 (45-0453-82), CD80-PE-Cy7 (25-0801-82), CD11c-PE-Cy7 (25-0114-82), CD4-PE-Cy7 (25-0041-82), CD8α-PE-Cy7 (25-0081-82), TCR-β-APC (17-5961-82), NK1.1-APC (17-5941-82), CD19-APC (17-0193-82), CD44-AF780 (47-0441-82), CD11b-AF780 (47-0112-82), CD86-EF450 (48-0862-82), MHC class II (I-A/I-E)-EF450 (48-5321-82), CD69-EF450 (48-0691-82), and CD4-EF450 (48-0042-82). Cells were stained for intracellular markers using the following eBioscience antibodies at 1:200 dilution: TNF-α-AF488 (53-7321-82), IFN-γ-PerCP-Cy5.5 (45-7311-82), and Ki67-PE-Cy7 (25-5698-82). The following eBioscience live/dead dyes were used at a 1:800 dilution: Fixable Viability Dye eFluor 780 (65-0865-14) and Fixable Viability Dye eFluor 506 (65-0866-18). For samples analyzed using the Cytek Aurora Flow Cytometry System, cells were stained for surface markers using the following antibodies at 1:200 dilution (except where indicated): CD45-AF700 , CD11b-BB700 , CD64-PE-Cy7 , CD19-BV711 , CD3e-BV711 , NK1.1-BV711 , Ly6G-BV711 , TER119-BV711 , CD11c-EF506 , MHC II (I-A/I-E)-SB780 , CD26-PE , XCR1-APC , SIRPα-SB436  (used at 1:100 dilution), CD103-BV605 , CD80-BV650 , CD86-APC-EF780 , TCR-β-APC , CD4-BV650 , CD8α-BV421 , CD45.1-BV711 , PD1-BV786 , TIM3-APC-H7 , LAG3-SB600 , CXCR3-PE-Cy7 , KLRG1-EF506 , CD69-AF700 , and CD103-PerCP-EF710 .Single-cell suspensions prepared from tissues or cerebrospinal fluid were pipetted into a 96-well plate and pelleted. Eight-color experiments were performed on a Gallios flow cytometer (Beckman Coulter) and prepared as follows: Cells were treated with 50 μl of Fc block  for 10 min at room temperature. Cells were then stained for surface markers and incubated with a fixable live/dead viability dye for 30 min at 4 °C. In experiments where SIINFEKL-specific CD85 cells per well and restimulated for 24 hr with soluble tachyzoite antigen (STAg) at 25 μg/ml. Cells were then incubated with brefeldin A  at 37 °C for 6 hr. Cells were washed and stained for surface markers, and then intracellular cytokine staining was performed. To prepare STAg, tachyzoites of the RH strain of T. gondii were purified from HFF cultures, filtered through a 5.0 μm filter (EMD Millipore), resuspended in 1 X PBS, and lysed by five freeze-thaw cycles. Protein concentration was determined by BCA assay (Pierce) and stock solutions were stored at –80 °C.Cells isolated from the deep cervical lymph nodes or brain were seeded at 2.5x10GFPNr4a1 (CD45.1 congenic) mice or OT-I (CD45.1 congenic) were pooled, mechanically dissociated, treated with RBC lysis solution (0.16 M NH4Cl), and passed through a 70 μm strainer (Corning). Then, OT-I cells were expanded in vitro as previously described (6 to 5x106 labeled OT-I cells were transferred to mice anesthetized with ketamine (100 mg/kg) and xylazine (10 mg/kg) by retro-orbital intravenous injection. For dye dilution experiments, cells were labeled with 10 μM CellTrace Violet  for 20 min at 37 °C prior to adoptive transfer.Spleens and lymph nodes from OT-I/escribed . Brieflyt-test was used to compare two experimental groups. A one-way ANOVA was performed to compare three or more experimental groups with a single independent variable. A two-way ANOVA was performed to compare three or more experimental groups with two independent variables. When data were pooled from multiple experiments, a randomized block ANOVA was performed using the lme4 software package in R  or RStudio (v1.1) statistical packages. Power analysis was performed in R using the pwr software package to calculate group sizes needed to achieve a power of 0.8, with effect size estimated from preliminary experiments. Randomization of samples was ensured by including mice from the same experimental group in different cages. A two-tailed student’s age in R . This te Toxoplasma gondii (T.g.) infection in mice. They present compelling data showing dendritic cell (DC) accumulation in the dura and CSF at 6 weeks post-infection, which matches with the replication peak of T.g. in the brain, and with T cell expansion/activation in the draining lymph node (dCLN). They also convincingly show that during chronic infection, antigen-specific T cells are generated not only in the dCLN but also in the periphery (ILN), which could account for the presence of T cells in the brain after surgical blockade of the lymphatics. This study highlights also how the CNS is protected against environmental challenges.Kovacs et al. provide important and valuable data on the role of meningeal lymphatic drainage in T cell responses during chronic  public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:Toxoplasma gondii but is dispensable for parasite control in the brain" for consideration by eLife. Your article has been reviewed by 2 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Betty Diamond as the Senior Editor. The following individual involved in the review of your submission has agreed to reveal their identity: Sarah Mundt (Reviewer #2).Thank you for submitting your article "Meningeal lymphatic drainage promotes T cell responses against The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revision:We all agree that the study warrants publication pending adequate revision.Please find below the key revision points that need to be addressed.1) A better gating strategy to quantify DC subsets with kinetics.2) A better definition of T cell responses with kinetics and fate of OT1/ dCLN generated T cell generated in the chronic versus acute phase.3) Kinetics of parasite replication in the periphery (e.g. in tissue draining to ILN) and in the dural meninges, for WT and/or Pru-OVA strains to provide a better context to understand the localization of T cell priming in chronic and acute phases.Reviewer #1 (Recommendations for the authors):1. In Figure 1, DC are quantified using CD11cYFP reporter, or CD11c gating strategy , which is not sufficient to prove that those are DCs . A better gating strategy  in the dura and the dCLN should be provided if the authors want to show that those DC are important for antigen transfer in the dCLN. Is there a correlation between DC number in the meninges and parasite load in the brain?+ cysts number) should be given in the brain, meninges, and peripheral tissues over time, to better understand in each model when and where the infection and thus the priming occurs. This should be part of Figure 1, to explain the model.2. The time course of both the WT strain and the attenuated strain loads .5. In Fig1q, MHC-II stain is everywhere and blurry, so it's hard to see colocalization.6. It's unclear why the authors looked at DC in the CSF and how they envision the role of CSF DC versus dural DC in priming?7. In Figure 2, why were 5 hours time point chosen? It seems too fast to have a full picture of migrating DCs , and too long to only look at soluble antigen drainage.8. T cell activation is sometimes looked at using IFNγ, or CD44/CD62L strategy, or CD69 . It's unclear why, and this makes the comparison more difficult. It would be interesting to have the total number of CD4 and CD8 also, independently of their activation status.9. It's convincing that there is a defect in T cell activation in the dCLN upon ligation . Visudyne treatment to locally delete meningeal lymphatics would have been a plus, to prove that this is through dural drainage.+ and CD4+ T cells?10. In Figure 4, I guess there are no changes neither in CD69+ or CD62L- T cells but have the authors checked? More importantly, what about exhausted and resident CD811. It would have been expected that because of the ligation, T cells would get stuck in the meninges. Have the authors quantified T cell accumulation in the meninges at 6w?12. In Figure 5, it's interesting to show that even in the chronic phase, T cells are still primed as antigen is still available. What is the contribution of these newly generated OT1 cells in the pool of brain T cells ? And what is the phenotype (activation/exhaustion/residence) of those OT1 generated in the chronic phase when they reach the brain? This would be relevant in the cancer field too.+ or CD8+ T cells the main drivers of parasite clearance (is the brain load higher upon CD4 or CD8 depletion?).13. Are CD414. The fact that T cells activated in the dCLN do not contribute substantially to the pool of brain T cells in the chronic phase could be expected, as the infection is given i.p. and as other organs seem chronically infected in the periphery. However, it would be interesting to address this question when the pathogen is mainly replicating in the CNS. Could the authors use icv injection of T.g.?15. It would also be interesting to look at experimental settings in which, during the chronic phase, only the brain is releasing antigen . The impact of those chronically primed T cells in the dCLN, if they are the only ones that can be generated, should be very interesting.Overall, this manuscript convincingly shows that drainage to the dCLN is required to activate dCLN T cells in the chronic phase, but those T cells do not seem to substantially contribute to the pool of brain T cells at this stage. However, some very interesting data could emerge from this model, by looking at the becoming of OT1 generated in the chronic versus acute phase. More importantly, it would be really interesting and impactful to address the role of those dCLN-generated T cells in the acute and chronic phases, in models where the CNS is the main source of antigen, in the acute or chronic phase. These new data would really bring novelty and impact to this study.Reviewer #2 (Recommendations for the authors):– The gating strategy shown in Figure 1 Suppl1 is for Cd11c+ MHCII+ APCs but does not allow to identify DCs. The MHCII staining looks a bit funky too. There's no real negative population. Can the authors comment on that? Can the authors also show MHCII vs dump?– In general, there hasn't been used a DC-specific marker combination to identify, characterise and distinguish DCs from other CD11c+ MHCII+ phagocytes (i.e. MdCs or BAMs). The authors should either stick to calling the cells dural APCs throughout the manuscript or perform additional experiments to characterise these cells better and more accurately (for example with an FC panel including CD26 to identify DCs and CD88 to discriminate from MdCs and XCR1 to distinguish cDC1s from cDC2s).– The authors show an increase in CD11c+ APCs in chronically infected mice, is coincident with chronic infection and increased parasite burden on the brain(?). What happens in the acute stage, e.g. 2 weeks after infection? T. gondii cysts in the dura mater – Independence of direct infection of the dura: Although, this finding is not central to the main message of the paper it would have been nice if that was supported by a second approach, e.g. microscopy, to exclude the presence of – In Figures 1k and m there seem to be a lot of Cd11c-YFP cells in naïve mice which can not be seen in Figure 1b. Can the authors comment on that?– DQ-OVA experiments are nice and convincing but such experiments have been performed previously. Can the authors provide additional information, for instance on the composition of APCs that have sampled Ag in the CNS and enter the lymphatic vessels in the dura mater?– The CSF data are really intriguing. I was just wondering about the CD80 and Cd86 expression and the FMO data. Was this gated on DCs (Cd11c+ MHCII+) minus CD80 in Figure 1-sup 2, c and Cd11c+ MHCII+ minus CD86 in Figure 1-sup 2, d, respectively? Can the authors show the raw data here? Also, the expression of Cd80 and Cd86 should be shown as MFI and not in frequency since you don't have an isolated population of CD80/86+ cells but rather a shift in the total cells.– Again, is it possible to distinguish and characterize DQ_OVA+ cells in the DCLNs? Are the CD11cMHCII cDC1s and/or cDC2s? Are there DQ-OVA+ B cells? + T cells as well?  (if not you can transfer of OT-I and OT-II cells for example and characterize their activation – cytokine response and proliferation (CTV dilution), etc.).– Is it possible to track OVA specific CD4– line 208-9 "deep cervical lymph nodes play a distinct role from other lymph nodes in supporting T cells responses …" – That's probably a bit misleading. The data rather suggest/confirm that there are distinct disease stages with the temporal change of the primary site of infection during chronification. The increased T cell responses in the DCLN at later stages just reflect the increased parasite load in the brain. The "role" of the LNs in supporting T cell responses is probably the same though (as stated correctly in 222-24).– The authors claim that dendritic cells number in the DCLNs are dramatically reduced after blockage of CNS Ag drainage . As mentioned above the use of Cd11c and MHCII is not sufficient to identify DCs. Are other cells also reduced? B cells for instance? Is there a cell type that is not reduced (negative control)?– The authors report a decreased activation of DCLNs DCs upon ligation of the lymphatic vessels. However, if they block the influx of activated DCs from the brain it is to be expected that there are fewer CD80/86 expressing cells in the LN . Hence the reduced frequency of CD80/86 expressing cells likely just reflects the reduction in activated APCs rather than a change of the phenotype. Can the authors show the raw data here too?I would expect that also here it's not possible to gate on CD80/86 positive cells but rather report a change in the MFI. This experiment doesn't really add much information but ok to show in the suppl. data.+ T cells, which is ok.– I wouldn't call the decrease of CD69+ T cells in the DCLNs "striking" (line 252). It is rather moderate, particularly for CD8T. gondii T cell immunity in the DCLNs. Unfortunately, the IFNγ data do not look very convincing . Can the authors include a noninfected control mouse a s well as an unstimulated sample? Maybe also use PMA/ionomycin stimulation as a positive control.– Similar to CD80/86 data for DCs, the phenotypic change of T cells in the DCLNs upon ligation is not surprising as the authors already showed that the influx of activated T cells is reduced. Nevertheless, it confirms the general message that CNS Ag drainage is required for anti-– Can the authors transfer OT-I and OT-II cells and determine the impact of lymphatic vessel ligation on Ag-specific proliferation and cytokine production during infection with the Pru-OVA strain?  (add to figure 3)– The time point of the ligation seems a bit arbitrary. What's the exact working hypothesis? Some thoughts: The parasite finds its way to the brain despite the presence of a functional T cell response. It is possible that without CNS drainage there would be more parasite load . Could the ligation during the infection phase have interfered with the seeding of the brain by itself and "dilute" the effect on parasite load by interfering with T cell responses in the DCLNs? Is it not also possible that reducing Ag drainage would result in a reactivation of the parasite? Can that happen at a later time point? Could the authors block Ag drainage during the chronic phase and look for T cell responses and parasite load at later time points? (e.g. ligation at 6-8 weeks and readout 3 and 6 weeks later?). Is the control of the parasite tachyzoites different from that of bradyzoites? Could the authors check for that (e.g. by qPCR for Bag1 and Sag1 or sth similar or maybe even by histology)?T. gondii T cell which enter the brain to control T. gondii seems logical, however, the narrative seemed a bit surprising since the inguinal lymph nodes were introduced as a "negative control" for T cell responses at later time points (during chronic infection). Can the authors show a naïve control of the Nur77GFP experiment – The explanation that T cell priming in the periphery is sufficient to lead to T-Gondii specific T cells responses in the CNS is plausible. Does the ligation affect the drainage of CNS Ag to other LNs? Are DC numbers and T cell activation affected by it? The explanation that peripheral Ag is sufficient to induce – The discussion seems a bit long and could be a bit more focussed (e.g. remove glymphatic flow part?) Essential revision:We all agree that the study warrants publication pending adequate revision.Please find below the key revision points that need to be addressed.1) A better gating strategy to quantify DC subsets with kinetics.+ cells using specific markers of type 1 and type 2 conventional dendritic cells . We developed a gating strategy using a framework defined by Guilliams et al. (2016) and consistent with well-established dendritic cell lineage markers . This gating strategy is provided in Figure 1 Supp 1. Briefly, we used a lineage dump gate to exclude T cells (CD3+), B cells (CD19+), NK cells (NK1.1+), neutrophils (Ly6G+), and erythroid cells (TER-119+) from our CD45+ population of interest. We then gated on the CD64- subset of CD11chiMHCIIhi cells to exclude macrophages (CD64+) that upregulated CD11c in the setting of inflammation. Next, we gated on CD26+ cells, which defines FLT3-dependent conventional dendritic cells . Finally, we gated on XCR1+SIRPα- cDC1s and XCR1-SIRPα+ cDC2s, markers that reliably track with expression of the cDC1 and cDC2 lineage-defining transcription factors IRF8 and IRF4, respectively . This gating strategy was employed for analysis of dendritic cells in the dural meninges  and for analysis of DQ-OVA+ dendritic cells in the DCLNs .We thank the reviewers for this critical suggestion, and we have addressed this concern by providing a more refined analysis of CD11cTo understand the kinetics of dendritic cell accumulation in the dural meninges, we quantified cDC1 and cDC2 number and frequency in naïve, acutely infected (2 wpi), and chronically infected (6 wpi) mice . We additionally examined the kinetics of dendritic cell activation by measuring cDC1 and cDC2 expression of CD80, CD86, and MHC class II . Interestingly, we did not observe a difference in cDC1 or cDC2 number or frequency between naïve and acutely infected mice. However, in chronically infected mice, there was a striking increase in cDC1 and cDC2 number and a shift in frequency of the two populations. Additionally, expression of co-stimulatory molecules peaked at 6 wpi. We also measured parasite burden in the brain and dural meninges at these same time points in order to determine whether there was a relationship between dendritic cell accumulation/activation and parasite burden in either tissue . In fact, expansion and activation of the cDC1 and cDC2 populations in the dural meninges corresponded to increased parasite burden in the brain at 6 wpi and not to parasite burden in the dural meninges. Indeed, the dural meninges lacked evidence of direct infection at 6 wpi both by real-time PCR and by fluorescent immunohistochemistry .In order to understand the functional capacity of cDC1s and cDC2s both in the dural meninges and in the draining deep cervical lymph nodes (DCLNs), we quantified the frequency of cDC1s and cDC2s at 6 wpi that harbored processed DQ-OVA either 2 h or 24 h after injection into the CSF . We chose these timepoints because soluble CSF-borne protein can be detected in the DCLNs within 2 h of i.c.m. injection in infected mice  and previous experiments have revealed that dendritic cells from the dural meninges traffic to the DCLNs by 24 h . Our studies demonstrated that cDC1s and cDC2s were equally capable of capturing CSF-derived protein during chronic brain infection.2) A better definition of T cell responses with kinetics and fate of OT1/ dCLN generated T cell generated in the chronic versus acute phase.T. gondii infection, including Trm-like cells . We examined the phenotype of both the transferred CD45.1+ T cell population and the endogenous CD45.1- SIINFEKL-specific CD8+ T cell population. Briefly, we observed low expression of co-inhibitory molecules on both the endogenous and transferred populations and, as expected, saw an increase in the memory subsets of endogenous parasite-specific T cells during chronic infection. The results of these experiments are shown in Figure 2 Supp 3 and Figure 2 Supp 4. We also examined expression of these markers on the polyclonal CD4+ and CD8+ T cell populations in sham or ligated mice, as shown in Figure 4 Supp 2, Figure 5 Supp 2, and Figure 5 Supp 3. From these experiments, we can conclude that there is a reduction in expression of co-inhibitory molecules in the DCLNs after ligation, consistent with a reduction in T cell activation, and no differences in co-inhibitory molecule expression or memory status in the brain after ligation.In order to characterize the phenotype of OT-Is generated in the DCLN and OT-Is that trafficked to the brain, we designed an experiment in which OT-I cells (CD45.1 congenic) were adoptively transferred to C57BL/6 mice either during acute infection (at 10 days post-infection) or during chronic infection (at 5 weeks post-infection) . Seven days later, we measured expression of relevant markers in the DCLNs and brain, including PD-1, TIM-3, and LAG-3, and markers that have been shown to define effector and memory-like T cells during 3) Kinetics of parasite replication in the periphery (e.g. in tissue draining to ILN) and in the dural meninges, for WT and/or Pru-OVA strains to provide a better context to understand the localization of T cell priming in chronic and acute phases.T. gondii persists in skeletal muscle during chronic infection, although detection by real-time PCR has demonstrated levels to be low or undetectable .We agree with the reviewers that this is an essential experiment. Therefore, following infection with Pru-OVA, we measured parasite burden by real-time PCR in several CNS and peripheral compartments at 7 days post-infection (dpi), 2 wpi, 3 wpi, and 6 wpi. These data are provided in Figure 2f, in order to provide context to the analysis of parasite-specific T cell responses in the deep cervical lymph nodes (DCLN) and inguinal lymph nodes (ILN) over the course of acute and chronic infection. Parasite burden was measured in the brain and dural meninges, as these sites are drained by the DCLNs, and in the subcutaneous tissue underlying the skin of the flank, as this site drains to the ILNs. Parasite burden was also measured in the DCLNs and ILNs themselves, which may be direct sites of infection themselves. Finally, parasite burden was measured in the quadriceps femoris skeletal muscle, as it has been reported that T. gondii antigen) is greatest in lymph nodes that drain peripheral tissues, such as the ILNs. The high levels of parasite gDNA in the ILNs likely reflects drainage of parasite or infected cells from infected peripheral tissues or direct infection of the lymph nodes themselves. During chronic infection, parasite could be detected only in the brain, and not in the dural meninges or skeletal muscle. These data explain the robust T cell responses in the DCLNs observed at 6 wpi  and suggest that the antigen-dependent T cell responses observed in the ILNs during chronic infection  may result from residual antigen in the ILNs persisting after the resolution of acute infection.We find that parasite burden is highest, among the tissues studied, in the inguinal lymph nodes during acute infection (7 dpi) and undetectable in the brain and dural meninges. By contrast, as infection progressed into the chronic stage, parasite burden increased in the brain and by 6 wpi was detectable only at this site. These results suggest that during acute infection, parasite (and Reviewer #1 (Recommendations for the authors):1. In Figure 1, DC are quantified using CD11cYFP reporter, or CD11c gating strategy , which is not sufficient to prove that those are DCs . A better gating strategy  in the dura and the dCLN should be provided if the authors want to show that those DC are important for antigen transfer in the dCLN. Is there a correlation between DC number in the meninges and parasite load in the brain?+ cells by spectral flow cytometry, using very specific markers of cDC1s and cDC2s. Our new gating strategy is discussed above . Like the reviewer, we were also interested in the question of whether DC number in the meninges tracked with parasite load in the brain or meninges. For this reason, we measured cDC1 and cDC2 number in naïve, acutely infected (2 wpi), and chronically infected (6 wpi) mice  and, in a separate cohort of mice, measured parasite burden by real-time PCR in the brain and dural meninges at these same time points . Interestingly, cDC1 and cDC2 accumulation in the dural meninges  corresponded to increased parasite burden in the brain and not the dural meninges. In fact, parasite gDNA was not detected in the dural meninges of any mice at 6 wpi and could only be detected in 4/7 mice at 2 wpi .The reviewer brings up an important point, and we have addressed this concern by providing a more refined analysis of CD11c+ cysts number) should be given in the brain, meninges, and peripheral tissues over time, to better understand in each model when and where the infection and thus the priming occurs. This should be part of Figure 1, to explain the model.2. The time course of both the WT strain and the attenuated strain loads .3. Fig1m is misleading, because there are more DCs around the sinuses in general after infection, not particularly around/in the lymphatics. If the authors were to quantify DC number in Lyve-1 negative area, they would still find an increase. So this does not prove that DCs are going through the lymphatics. As this has already been shown anyway by Kipnis group, they should refer to their study.+ number in both the LYVE1+ area and the LYVE1- area and that this makes it challenging to conclude that dendritic cells trafficking through the vessels is increased with infection. We have clarified this point in the text and referred to the Kipnis study that already demonstrated dendritic cell trafficking through these vessels to the deep cervical lymph nodes .We concede that there is an increase in the CD11c4. From Fig1p, it's unclear how the uptake is calculated to be 40% (it looks like 90% to me).+ and DQ-OVA- dendritic cell populations, consistent with the quantification shown in Figure 1 Supp 2j.We apologize for this inconsistency. In order to achieve a more precise picture of how cDC1s and cDC2s participate in CSF-borne antigen capture, this experiment was completed again using our new gating strategy for dendritic cells. These data are now presented in Figure 1 Supp 2h-j, and we have aimed to provide clearer and more representative flow plots showing the DQ-OVA5. In Fig1q, MHC-II stain is everywhere and blurry, so it's hard to see colocalization.We thank the reviewer for identifying this difficulty in interpretation and we agree. Therefore, we have a provided an alternative representative image  that we believe is clearer.6. It's unclear why the authors looked at DC in the CSF and how they envision the role of CSF DC versus dural DC in priming?The reviewer’s point is well taken. We have changed our language in the text to make the rationale for this experiment more clear. In short, seminal studies by the Kipnis lab demonstrated that dendritic cells injected into the CSF exit the CNS through meningeal lymphatic vessels . Because we observed an increase in the number of CD11c+ cells in the area of the meninges around the lymphatic vessels, we sought to determine whether dendritic cells were present in the CSF. Though this experiment does not directly address the different functions of CSF and dural APCs, we believe our findings represent a valuable first step towards understanding the distinct functions of APCs in the different compartments of the CNS and CNS border tissues.7. In Figure 2, why were 5 hours time point chosen? It seems too fast to have a full picture of migrating DCs , and too long to only look at soluble antigen drainage.+ cDC1s and cDC2s decreased from 30% at 2 h to 5% at 24 h in the dural meninges but did not change in the DCLNs, it remains unclear whether a large portion of DQ-OVA+ cells migrated from the dura or if the fluorescent signal produced by DQ-OVA cleavage products declines over time with additional processing.The 5-hour time point was selected based on a pilot experiment used to identify when emission of digested DQ-OVA products becomes detectable in the dural meninges. We agree with the reviewer’s criticism that this time point limits our ability to discriminate between drainage of soluble antigen and transport of antigen by migratory DCs, although the gold standard would be to design an experiment using photoconvertible dendritic cells, as was already performed by Louveau et al. in naïve animals (2018). Nonetheless, in order to achieve a preliminary understanding of whether DQ-OVA emission in the DCLNs is dependent on drainage of soluble antigen or transport via migratory DCs, we performed a new set of experiments examining the presence of CSF-derived DQ-OVA within cDC1s and cDC2s at 2 h and 24 h after i.c.m. injection . However, because the frequency of DQ-OVA8. T cell activation is sometimes looked at using IFNγ, or CD44/CD62L strategy, or CD69 . It's unclear why, and this makes the comparison more difficult. It would be interesting to have the total number of CD4 and CD8 also, independently of their activation status.hiCD62Llo or CD69 was based on the kinetics of upregulation of these molecules on activated T cells. Because antigen-experienced CD44hiCD62Llo T cells continue to exhibit this phenotype after activation, measuring the total number of CD44hiCD62Llo T cells provided insight into how the overall magnitude of the T cell response evolves in the DCLNs and ILNs over the course of infection. For the ligation studies, however, we were interested in identifying changes in activation that occurred in a short window of time , and measuring CD69 proved to be a more sensitive read-out for this because CD69 is upregulated only on the most recently activated T cells (Simms and Ellis 1996). The reason for examining proliferation and cytokine expression was to understand how restriction of meningeal lymphatic outflow affected not just markers of T cell activation but also functional read-outs of T cell activation and T cell effector capacity. As suggested, we included the total number of CD4+ and CD8+ T cells in the DCLNs after ligation .We apologize that the rationale for these parameters was not clear. The decision to assess activation status of T cells using CD449. It's convincing that there is a defect in T cell activation in the dCLN upon ligation . Visudyne treatment to locally delete meningeal lymphatics would have been a plus, to prove that this is through dural drainage.We agree that Visudyne would have been an outstanding complementary approach for demonstrating dependence of T cell responses on meningeal lymphatic vessels. Unfortunately, we did not have access to the instrumentation required for completing this experiment.+ and CD4+ T cells?10. In Figure 4, I guess there are no changes neither in CD69+ or CD62L- T cells but have the authors checked? More importantly, what about exhausted and resident CD8+ and CD8+ T cells entering the brain are CD44hiCD62Llo. Following ligation, we did not observe differences in the activation status of T cells in the brain, and we have included these data in Figure 5 Supp 1. We also examined markers of T cell exhaustion  and report decreased expression of these molecules in the DCLNs  and no differences in expression of these molecules in the brain  following ligation. We examined CD69+CD103+ Trm-like cells  and report no differences in the brain after ligation .As other groups have reported , we find that almost the entire population of CD411. It would have been expected that because of the ligation, T cells would get stuck in the meninges. Have the authors quantified T cell accumulation in the meninges at 6w?+ and CD8+ T cell numbers in the meninges and observed no differences after ligation. These data may reflect alternative outflow routes, such as the superficial cervical lymph nodes, or lack of survival of retained T cells.We examined CD412. In Figure 5, it's interesting to show that even in the chronic phase, T cells are still primed as antigen is still available. What is the contribution of these newly generated OT1 cells in the pool of brain T cells ? And what is the phenotype (activation/exhaustion/residence) of those OT1 generated in the chronic phase when they reach the brain? This would be relevant in the cancer field too.T. gondii infection, including Trm-like cells . The results of these experiments are shown in Figure 2 Supp 3 and Figure 2 Supp 4 and described above .In order to characterize the phenotype of OT-Is generated in the DCLN and OT-Is that trafficked to the brain, we designed an experiment in which OT-I cells (CD45.1 congenic) were adoptively transferred to C57BL/6 mice either during acute infection (at 10 days post-infection) or during chronic infection (at 5 weeks post-infection) . Seven days later, we measured expression of relevant markers in the DCLNs and brain, including PD-1, TIM-3, and LAG-3, and markers that have been shown to define effector and memory-like T cells during + or CD8+ T cells the main drivers of parasite clearance (is the brain load higher upon CD4 or CD8 depletion?).13. Are CD4+ and CD8+ T cells are both essential for parasite clearance and host survival during the chronic stage of infection. Studies performed by the Sher group demonstrated that combined depletion of CD4+ and CD8+ T cells leads to rapid mortality of chronically infected mice and depletion of either CD4+ or CD8+ T cells leads to increased parasite burden in the brain .CD414. The fact that T cells activated in the dCLN do not contribute substantially to the pool of brain T cells in the chronic phase could be expected, as the infection is given i.p. and as other organs seem chronically infected in the periphery. However, it would be interesting to address this question when the pathogen is mainly replicating in the CNS. Could the authors use icv injection of T.g.?We agree with the reviewer that confining infection to the brain would be an excellent proof-of-concept experiment to determine whether CNS lymphatic drainage to the DCLNs becomes more important when peripheral sources of antigen are minimized. We attempted this experiment by directly injected parasite into the cortex. However, in our pilot study, the mice reached their humane endpoint within 9 days, and by this time, only one of three mice had mounted a parasite-specific T cell response in the brain.15. It would also be interesting to look at experimental settings in which, during the chronic phase, only the brain is releasing antigen . The impact of those chronically primed T cells in the dCLN, if they are the only ones that can be generated, should be very interesting.We agree with the reviewer that this would be a valuable experiment. Although the transgenic strain of parasite needed to make this experiment feasible is being developed by other groups—one that expresses OVA under the control of the bradyzoite-specific BAG1 promoter—this tool is unfortunately not yet available.Overall, this manuscript convincingly shows that drainage to the dCLN is required to activate dCLN T cells in the chronic phase, but those T cells do not seem to substantially contribute to the pool of brain T cells at this stage. However, some very interesting data could emerge from this model, by looking at the becoming of OT1 generated in the chronic versus acute phase. More importantly, it would be really interesting and impactful to address the role of those dCLN-generated T cells in the acute and chronic phases, in models where the CNS is the main source of antigen, in the acute or chronic phase. These new data would really bring novelty and impact to this study.Reviewer #2 (Recommendations for the authors):– The gating strategy shown in Figure 1 Suppl1 is for Cd11c+ MHCII+ APCs but does not allow to identify DCs. The MHCII staining looks a bit funky too. There's no real negative population. Can the authors comment on that? Can the authors also show MHCII vs dump?hiMHC IIhi cells as dendritic cells. For this reason, we completed a new analysis of dendritic cells in the dural meninges and DCLNs using a more precise gating strategy, as described above in the Editor’s Essential Revisions, Point 1. We also provide in We agree with the reviewer that our gating strategy for antigen-presenting cells was not sufficient to accurately identify the population of CD11c– In general, there hasn't been used a DC-specific marker combination to identify, characterise and distinguish DCs from other CD11c+ MHCII+ phagocytes (i.e. MdCs or BAMs). The authors should either stick to calling the cells dural APCs throughout the manuscript or perform additional experiments to characterise these cells better and more accurately (for example with an FC panel including CD26 to identify DCs and CD88 to discriminate from MdCs and XCR1 to distinguish cDC1s from cDC2s).We agree with the reviewer and have provided a description of our new gating strategy above, in the Editor’s Essential Revisions, Point 1.– The authors show an increase in CD11c+ APCs in chronically infected mice, is coincident with chronic infection and increased parasite burden on the brain(?). What happens in the acute stage, e.g. 2 weeks after infection? As described above , we observed an increased accumulation of cDC1s and cDC2s in the dural meninges during chronic infection, and this increase in number corresponded to increased parasite burden in the brain but not the meninges . There is no difference in cDC1 or cDC2 number in the dural meninges of naive and acutely infected mice (2 wpi). With the exception of a mild increase in CD80 expression by cDC2s during acute infection, upregulation of co-stimulatory molecules and MHC class II occurred during chronic infection (6 wpi) .T. gondii cysts in the dura mater – Independence of direct infection of the dura: Although, this finding is not central to the main message of the paper it would have been nice if that was supported by a second approach, e.g. microscopy, to exclude the presence of We appreciate the reviewer’s suggestion and have provided representative images demonstrating the absence of parasite in the dural meninges during chronic infection using a polyclonal α-ME49 antibody .– In Figures 1k and m there seem to be a lot of Cd11c-YFP cells in naïve mice which can not be seen in Figure 1b. Can the authors comment on that?We apologize for this confusion. The apparent discrepancy resulted from poor downsampling of the tilescan when being prepared for the PDF file. In order to resolve this issue, we enlarged the tilescan and increased the pixel density to 450 ppi .– DQ-OVA experiments are nice and convincing but such experiments have been performed previously. Can the authors provide additional information, for instance on the composition of APCs that have sampled Ag in the CNS and enter the lymphatic vessels in the dura mater?+ cells remained equivalent in the DCLNs at 2 h and 24 h post-injection, despite falling from 30% to 5% in the dural meninges for both cDC1s and cDC2s.We appreciate the reviewer’s suggestion and have followed up our initial DQ-OVA studies with new experiments examining the presence of DQ-OVA in cDC1s and cDC2s . These experiments revealed that cDC1s and cDC2s were equally capable of capturing CSF-derived protein during chronic brain infection and showed that the frequency of DQ-OVA– The CSF data are really intriguing. I was just wondering about the CD80 and Cd86 expression and the FMO data. Was this gated on DCs (Cd11c+ MHCII+) minus CD80 in Figure 1-sup 2, c and Cd11c+ MHCII+ minus CD86 in Figure 1-sup 2, d, respectively? Can the authors show the raw data here? Also, the expression of Cd80 and Cd86 should be shown as MFI and not in frequency since you don't have an isolated population of CD80/86+ cells but rather a shift in the total cells.+ and CD86+ CD11chiMHC IIhi cells isolated from the CSF and the positive populations were determined using FMOs for CD80 and CD86. We elected to examine frequency rather than MFI in order to gauge what proportion of the overall APC population expressed any level of these co-stimulatory molecules. Lacking a comparison group (APCs were absent in the CSF of naïve mice), we believed this read-out would be more informative than MFI alone. The raw data, including the FMOs used for gating and the quantification, are now shown in Figure 1 Supp 3c-e.We apologize for the confusion regarding the gating strategy and quantification. Indeed, we measured frequency of CD80– Again, is it possible to distinguish and characterize DQ_OVA+ cells in the DCLNs? Are the CD11cMHCII cDC1s and/or cDC2s? Are there DQ-OVA+ B cells? We appreciate the reviewer’s suggestion and have provided a more detailed analysis of the APCs that harbor DQ-OVA in the DCLNs, as explained above in Point 6. The frequencies of cDC1s and cDC2s in the DCLNs that harbored DQ-OVA digestion products 2 or 24 h after i.c.m. injection were equivalent, as shown in Figure 2 Supp 1.+ T cells as well?  (if not you can transfer of OT-I and OT-II cells for example and characterize their activation – cytokine response and proliferation (CTV dilution), etc.).– Is it possible to track OVA specific CD4+ T cells or OT-II cells cannot be readily tracked in our C57BL/6 mouse model of infection. It is for this reason that most groups studying T. gondii infection in C57BL/6 mice track parasite-specific T cell responses using the MHC I-SIINFEKL tetramer and the OT-I transfer system .Unfortunately, OVA-specific CD4– line 208-9 "deep cervical lymph nodes play a distinct role from other lymph nodes in supporting T cells responses …" – That's probably a bit misleading. The data rather suggest/confirm that there are distinct disease stages with the temporal change of the primary site of infection during chronification. The increased T cell responses in the DCLN at later stages just reflect the increased parasite load in the brain. The "role" of the LNs in supporting T cell responses is probably the same though (as stated correctly in 222-24).We completely agree with the reviewer and have removed this language from the text. We conclude, instead, that “[t]hese results likely reflect the distinct sources of antigen that each lymph node site drains during the different stages of infection.”– The authors claim that dendritic cells number in the DCLNs are dramatically reduced after blockage of CNS Ag drainage . As mentioned above the use of Cd11c and MHCII is not sufficient to identify DCs. Are other cells also reduced? B cells for instance? Is there a cell type that is not reduced (negative control)?We performed the experiment again using our refined gating strategy for cDC1s and cDC2s and interestingly observed no difference in the total number of cDC1s or cDC2s in the DCLNs after ligation . However, we did observe a significant reduction in the frequency and number of CD103+ cDC1s and a trending decrease in the frequency and number of CD103+ cDC2s after ligation . These results are consistent with the CD103+ subset representing a migratory dendritic cell population that trafficked from the dural meninges.– The authors report a decreased activation of DCLNs DCs upon ligation of the lymphatic vessels. However, if they block the influx of activated DCs from the brain it is to be expected that there are fewer CD80/86 expressing cells in the LN . Hence the reduced frequency of CD80/86 expressing cells likely just reflects the reduction in activated APCs rather than a change of the phenotype. Can the authors show the raw data here too?I would expect that also here it's not possible to gate on CD80/86 positive cells but rather report a change in the MFI. This experiment doesn't really add much information but ok to show in the suppl. data.After performing this experiment using our refined gating strategy for cDC1s and cDC2s, we found that even though there is no difference in the total number of cDC1s and cDC2s in the DCLNs, the expression of co-stimulatory molecules by these cells is significantly reduced . This difference may be the result of reduced trafficking of activated dendritic cells to the DCLNs, but it also raises the question as to whether pro-inflammatory factors draining from the brain, CSF, or meninges contribute to the activation of lymphoid-resident DCs. As the reviewer suggests, we have provided the raw data and reported expression as MFI.+ T cells, which is ok.– I wouldn't call the decrease of CD69+ T cells in the DCLNs "striking" (line 252). It is rather moderate, particularly for CD8Per the reviewer’s suggestion, we have changed the language of the text in order to avoid the misleading characterization of the change as “striking”.T. gondii T cell immunity in the DCLNs. Unfortunately, the IFNγ data do not look very convincing . Can the authors include a noninfected control mouse a s well as an unstimulated sample? Maybe also use PMA/ionomycin stimulation as a positive control.– Similar to CD80/86 data for DCs, the phenotypic change of T cells in the DCLNs upon ligation is not surprising as the authors already showed that the influx of activated T cells is reduced. Nevertheless, it confirms the general message that CNS Ag drainage is required for anti-+ T cells. We have thus provided unstimulated CD4+ and CD8+ T cells as negative controls (“No STAg”), which should help with the interpretation of these data .We appreciate the reviewer’s concerns, in particular given the low degree of IFN-γ expression by CD8– Can the authors transfer OT-I and OT-II cells and determine the impact of lymphatic vessel ligation on Ag-specific proliferation and cytokine production during infection with the Pru-OVA strain?  (add to figure 3)+ T cell population after ligation . This disparity may reflect the self-selecting nature of proliferative (CTV+) cells, which would become overrepresented in the OT-I population as OT-I cells that fail to proliferate die off.We performed this experiment and observed a trending decrease in the total number of OT-Is in the DCLNs after ligation but no difference in the total number of OT-Is in the brain , d. Addi– The time point of the ligation seems a bit arbitrary. What's the exact working hypothesis? Some thoughts: The parasite finds its way to the brain despite the presence of a functional T cell response. It is possible that without CNS drainage there would be more parasite load . Could the ligation during the infection phase have interfered with the seeding of the brain by itself and "dilute" the effect on parasite load by interfering with T cell responses in the DCLNs? Is it not also possible that reducing Ag drainage would result in a reactivation of the parasite? Can that happen at a later time point? Could the authors block Ag drainage during the chronic phase and look for T cell responses and parasite load at later time points? (e.g. ligation at 6-8 weeks and readout 3 and 6 weeks later?). Is the control of the parasite tachyzoites different from that of bradyzoites? Could the authors check for that (e.g. by qPCR for Bag1 and Sag1 or sth similar or maybe even by histology)?One of the limitations of the ligation approach is the possibility that collateral vessels might reroute lymph flow around the ligated vessels and reduce the length of time for which our approach to blocking meningeal lymphatic outflow remains efficacious . We demonstrated that ligation effectively blocks CSF outflow to the DCLNs for three weeks . With this interval in mind, we decided to perform ligation at three weeks post-infection when T cells begin to display a response against the parasite in the DCLNs , a point we have made more clear in the text. We do not believe that ligation would have a major impact on parasite seeding of the brain because parasite burden in the blood peaks between 7-10 dpi and parasite has been cleared from peripheral tissues by 3 wpi . To assess whether ligation affected control of tachyzoites or bradyzoites differentially, we measured total parasite gDNA by real-time PCR  and cyst count by microscopy . Because there was no difference in total parasite gDNA or cyst number, it is unlikely that there is a difference in tachyzoite or bradyzoite burden.T-Gondii specific T cells responses in the CNS is plausible. Does the ligation affect the drainage of CNS Ag to other LNs? Are DC numbers and T cell activation affected by it? The explanation that peripheral Ag is sufficient to induce T. gondii T cell which enter the brain to control T. gondii seems logical, however, the narrative seemed a bit surprising since the inguinal lymph nodes were introduced as a "negative control" for T cell responses at later time points (during chronic infection). Can the authors show a naïve control of the Nur77GFP experiment – The explanation that T cell priming in the periphery is sufficient to lead to + or CD8+ T cell activation . Because the SCLNs represent another outflow site, we also tested whether blocking drainage to both the DCLNs and SCLNs would have an impact on the T cell response in the brain . However, there was no difference in CD4+ or CD8+ T cell number in the brain , providing additional support to the conclusion that meningeal lymphatic drainage is dispensable for T cell responses in the brain, and that T cell responses at peripheral sites are likely playing an important role in sustaining T cell responses in the brain.The reviewer brings up an excellent point. The DCLNs are not the only drainage site for CSF. Other groups have shown that the superficial cervical lymph nodes (SCLNs) also drain components of the CSF . As suggested, we tested whether ligation of the lymphatic vessels afferent to the DCLNs affects drainage of CSF-derived antigen to the SCLNs or T cell responses in these nodes. Indeed, we observed no change in outflow  and no change in CD4– The discussion seems a bit long and could be a bit more focussed (e.g. remove glymphatic flow part?)We agree with the reviewer’s comment and have removed the discussion of glymphatic flow to be more focused.ReferencesBlum, K. S., S. T. Proulx, P. Luciani, J. C. Leroux and M. Detmar (2013). "Dynamics of lymphatic regeneration and flow patterns after lymph node dissection." Breast Cancer Res Treat 139(1): 81-86.Chu, H. H., S. W. Chan, J. P. Gosling, N. Blanchard, A. Tsitsiklis, G. Lythe, N. Shastri, C. Molina-Paris and E. A. Robey (2016). "Continuous Effector CD8(+) T Cell Production in a Controlled Persistent Infection Is Sustained by a Proliferative Intermediate Population." Immunity 45(1): 159-171.Djurkovic-Djakovic, O., V. Djokic, M. Vujanic, T. Zivkovic, B. Bobic, A. Nikolic, K. Slavic, I. Klun and V. Ivovic (2012). "Kinetics of parasite burdens in blood and tissues during murine toxoplasmosis." 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For selecting features that allow differentiation of clinical response, a stepwise dimension reduction was performed. Logistic regression models were fitted and selected PRE-/DELTA-RF were tested for their predictive value. QoL improved significantly after percutaneous sclerotherapy. While no common baseline patient characteristics were able to predict response to percutaneous sclerotherapy, the radiomics signature of VMs (independent PRE/DELTA-RF) revealed high potential for the prediction of clinical response after percutaneous sclerotherapy. This proof-of-concept study provides first evidence on the potential predictive value of (delta) radiomic analysis from diffusion-weighted MRI for Quality-of-Life outcome after percutaneous sclerotherapy in patients with venous malformations.Prediction of response to percutaneous sclerotherapy in patients with venous malformations (VM) is currently not possible with baseline clinical or imaging characteristics. This prospective single-center study aimed to predict treatment outcome of percutaneous sclerotherapy as measured by quality of life (QoL) by using radiomic analysis of diffusion-weighted (dw) magnetic resonance imaging (MRI) before and after first percutaneous sclerotherapy. In all patients ( Venous malformations (VM) are slow-flow vascular malformations according to the ISSVA  classification, with a prevalence of up to 1% in the overall population ,3. VM arTherefore, early identification of responders and non-responders to percutaneous sclerotherapy is crucial. Currently, no reliable baseline clinical or imaging parameters exist to predict patient outcome following percutaneous sclerotherapy. Imaging in VMs is based on ultrasound and magnetic resonance imaging (MRI) . Since dTherefore, this study aims to evaluate the predictive value of radiomic features obtained from pre- and post-interventional dw-MRI in evaluating outcome of percutaneous sclerotherapy of VM by means of patients’ quality-of-life improvement. This study was performed as a prospective single-center observational proof-of-concept study at a tertiary care vascular anomalies center. All patients with venous malformations of the upper or lower limb who had never been treated by percutaneous sclerotherapy before and who were not treated otherwise for the past 12 months were consecutively included between March 2020 and June 2021. Patients with mix-type vascular malformations were excluded. Children too young for MRI without sedation or anesthesia were also excluded. Diagnosis of VM was based on clinical and imaging  assessment. Percutaneous sclerotherapy was performed in all patients for clinical indications after interdisciplinary vascular anomalies board discussion independent of the presented study. Patient data and procedural data were retrieved from the Clinical and Radiological Information System  and Picture Archiving and Communication System (PACS). The study was approved by the Institutional Review Board (ID: 2019-515-f-S). MRI was performed within 48 h before and 24 h after first percutaneous sclerotherapy of the VM. All imaging examinations were conducted on a 1.5 T scanner  with an anterior coil and a build-in posterior coil (32 channels) covering the entire VM  or general anesthesia. For percutaneous sclerotherapy, one to five appropriate locations of VMs were sequentially identified under ultrasound-guidance. Intravascular placement of the inserted 22 G needle was assured with aspiration of venous blood and injection of contrast medium under fluoroscopy, confirming appropriate distribution within the venous malformation and excluding extravasation. Sclerotherapy was performed with gelified ethanol  and/or polidocanol foam . Percutaneous sclerotherapy was repeated after 4 to 6 weeks if it was technically feasible, patients reported restricting symptoms, mostly pain, or no further improvement in patients’ symptoms was gained after sclerotherapy. All procedural data and patient recordings of performed interventional procedures were analyzed with regard to age, sex, localization (upper/lower limb), number of used accesses (needle locations) during sclerotherapy, type and amount of sclerosing agent, as well as any minor or major adverse events according to the Common Terminology Criteria for Adverse Events, version 5.0 classification.Clinical outcome and quality-of-life were assessed using two standardized questionnaires (SF-36 and TESS score) at baseline, four weeks after the first interventional treatment of the venous malformation and at latest available follow-up  effectiveness of first percutaneous sclerotherapy and (2) effectiveness of repetitive percutaneous sclerotherapy. Effectiveness of the first percutaneous sclerotherapy was defined by two outcome parameters: first, improvement in SF-36 pain score by at least 20 points and second, improvement in TESS score by at least 5% each four weeks after first sclerotherapy compared to baseline. Effectiveness of repetitive percutaneous sclerotherapy was defined by two outcome parameters: first, achieving a SF-36 pain score of at least 85 points (meaning pain only rarely or in severe stress situations) and second, by achieving a TESS score of 85% or higher. Two experienced radiologists, blinded for interventional and clinical data, independently evaluated pre- and post-interventional MRI data in a random order. For image segmentation, the reader-specific label map volume based on the VM volume in T2-weighted images was transferred to diffusion-weighted-MRI sequences. Radiomic features from labelled dw-MRI sequences (ADC) were extracted twice, each by the same independent readers for inter-observer analysis, and included 162 first-order logic features and 216 gray level co-occurrence matrix (GLCM) features, as described elsewhere . The radn = 378) in comparison to the number of patients (n = 16), feature selection and dimension reduction were performed separately for PRE-RF and DELTA-RF [Due to the exceeding number of radiomic features , previous therapies, number of accesses during sclerotherapy, sclerosing agent , the quantity of the agent in mL, and the number of performed therapies were analyzed regarding their influence on patient outcome  with a binary logistic regression using IBM SPSS statistics  for metric and categorial predictors, respectively. Statistical analysis of the QoL data was performed using Prism 9 software . A p-value of < 0.05 was considered significant. All data are presented as mean ± standard deviation or as median (and range), as appropriate. The paired student Sixteen consecutive patients  undergoing percutaneous sclerotherapy for venous malformation were included in this study. Nine patients (56.25%) had a VM of the upper extremity, seven patients (43.75%) of the lower extremity. Three patients had a history of previous treatment at least 9 or more years ago  and one laser therapy (2012)). Only one patient received additional laser therapy after sclerotherapy (patient 2); all other patients had no further treatment. Median follow up was 12 months after the first treatment, range 5–20 months. Last quality-of-life assessment was at least 4 weeks after last treatment. Detailed information on patient characteristics and follow-up can be found in A mean of 2.6 ± 1.1 (range 1–4) percutaneous sclerotherapies were performed per patient. Patients received sclerotherapy in a mean of 2.7 ± 1.4 locations per session, range 1–5. In the first therapy cycle, six patients received only gelified ethanol with a dose of 1.9 ± 1.1 mL, while seven patients were treated with polidocanol alone, with a dose of 2.9 ± 1.1 mL. The remaining three patients were treated with a combination of 2.3 ± 0.6 mL gelified ethanol and 1.7 ± 0.6 mL polidocanol. No major adverse events were observed during or after the intervention, and minor adverse events included post-interventional pain and local inflammation. No procedure-associated short- or long-term adverse events, such as necrosis or nerve damage, were observed during follow-up. p-value 0.0009). Thus, the improvement led to score values close to the maximum of 100%. The more-detailed SF-36 survey achieved a significant increase in the score values in all assessed categories after repetitive sclerotherapy as well. In detail, the score for physical functioning significantly improved from 72.8 ± 23.3 to 93.1 ± 11.1 , while the score for the role limitations due to physical health increased significantly from 51.6 ± 38 to 89.1 ± 20.4 . Three patients did not sufficiently improve in these categories, but already had rather high baseline scores for physical functioning of 75 or more. With the SF-36 score, the effects of physical disease on mental health are also evaluated, as characterized by the following categories: role limitations due to emotional problems, energy/fatigue, emotional well-being and social functioning. All four categories improved significantly after repetitive sclerotherapy, from 60.4 ± 45.9 to 93.8 ± 25 , from 56.9 ± 17.5 to 72.8 ± 20.9 , from 57.5 ± 24.1 to 75.0 ± 18.0 , and from 82.8 ± 25.0 to 92.2 ± 15.1 , respectively. Additionally, repetitive percutaneous sclerotherapy led to a significant improvement of pain, yielding an increase in SF-36 score from 23.3 ± 16.7 to 70.3 ± 24.8 . Here, half of the patients had a score of 80 or higher at final follow-up, which means pain occurs only in situations with increased stress, such as extensive participation in sports or long walks. As an overall score, the general health score improved significantly from 50.3 ± 22.6 to 73.8 ± 16.8 . Furthermore, patients reported a considerably more positive outlook regarding their expectations for future health change with a score increasing from 26.6 ± 25.0 at baseline to 79.7 ± 22.8 after repetitive sclerotherapy . In summary, defined quality-of-life outcome parameters were achieved as follows: eight patients (50%) improved in pain score by at least 20 points and six patients (37.5%) showed an improvement in TESS score of at least 5% after first sclerotherapy. Meanwhile, seven patients (43.75%) achieved a SF-36 pain score of 85 or higher, and 10 patients (62.5%) achieved a TESS score of 85% or higher at last follow up after repetitive sclerotherapy. All other patients were defined as non-responders for further analysis.Detailed quality-of-life data at baseline, four weeks after first sclerotherapy and at last follow-up at least four to six weeks after the last sclerotherapy, can be found in p-values > 0.05, see Binary logistic regression identified none of the analyzed common clinical parameters such as age, sex, location of VM, prior therapies, number of accesses during sclerotherapy, type or amount of sclerotic agent used, or number of performed sclerotherapies as predictive for any of the above defined quality-of-life outcome measures  and the feature minimum was identified for an achieved TESS score of at least 85%  was performed to predict outcome after sclerotherapy of VM. Subsequent to the multistep dimension reduction from pre-interventional dw-MRI data only, independent PRE-RF related to each of the defined outcome goals were identified . Regardileast 5% . Regardieast 85% . When asrange was identified, discriminating responders from non-responders regarding an increase in SF-36 pain score by at least 20 points. Further, for an increase in TESS score after first sclerotherapy by at least 5%, six independent features  were identified  were identified with respect to achieving a SF-36 pain score of 85 or higher. Again, the correlation matrix revealed closely correlating features . When assessing the predictive value of these DELTA-RF, the ROC analysis for the discrimination of responders and non-responders to the chosen response criterion each revealed an accuracy with an AUC of 1, respectively.Radiomic features are written in italics for easy identification. In a next step, delta radiomics analysis from dw-MRI data before and after the first percutaneous sclerotherapy of VM was performed to predict outcome after sclerotherapy, obtaining DELTA-RF after the multistep dimension reduction . Regardientified . As clusentified , represefeatures , wherebyAlthough venous malformations (VM) are benign lesions, they may cause severe symptoms such as pain, swelling, or functional impairment once symptomatic. As congenital lesions with a high rate of recurrence after therapy or the impossibility of definitive cure, VM often accompany patients’ lives over a tedious period with alternating or chronic symptoms . Thus, pPercutaneous sclerotherapy has been established as a minimally invasive strategy with good outcomes and a low risk profile , fosteriTherefore, this study evaluated the feasibility of using quantitative tissue parameters extracted from pre- (PRE-RF) and post-interventional (DELTA-RF) dw-MRI for response prediction to percutaneous sclerotherapy, as diffusion-weighted (dw) imaging with calculation of the apparent diffusion coefficient is a sensitive MRI method to detect venous malformations . Dw-MRI range, minimum, maximum) indicate that the heterogeneity of the untreated VMs in the baseline dw-MRI scan is predicting outcome of sclerotherapy. This notion fits well with the clinically observed heterogeneity of these lesions. Hence, once confirmed in larger prospective studies, these features may guide therapeutic decision for or against starting a treatment with percutaneous sclerotherapy.Using radiomics analysis of baseline dw-MRI as well as change in dw-MRI data after sclerotherapy, this study identified several (pre- or delta-) radiomic features significantly associated with treatment response  after either first sclerotherapy or repetitive cycles of sclerotherapy. In detail, identified pre-interventional features , thereby results are in line with observations for baseline radiomics analysis, and more advanced features of heterogeneity such as change in zone percentage were identified as associated with outcome response of percutaneous sclerotherapy. Exemplarily, this feature was also found to be relevant in response prediction to neo-adjuvant chemoradiation of lymph node metastases in non-small cell lung cancer (NSCLC) [Further, delta-radiomics analysis identified several features associated again with changes in heterogeneity ( (NSCLC) . Hence, Both baseline and delta radiomics analysis emphasize the potential of dw-MRI to guide treatment decision and therapy monitoring via assessing imaging biomarkers beyond the common anatomical information and including the advantages of a non-invasive diagnostic tool without the need for radiation or contrast agents, which is of benefit considering the usually young patient cohort with the need for repetitive imaging . TherebyThe presented study has several limitations. First, it is limited by a small patient cohort in a single vascular anomalies center, resulting in a small number of patients for the training and test set of the performed radiomics analysis. Although a multistep dimension reduction approach was only performed in the training dataset to ensure the generalizability of the statistical model, the number of patients in the test dataset is small. The AUC of 1 achieved in the prediction performance analysis is therefore due to the small test cohort and is not intended to suggest that a perfect model has been developed here. However, considering the rarity of disease, inclusion of only untreated and symptomatic patients with VMs of the limbs old enough to perform MRI on the identical scanner before and after sclerotherapy, without the need for sedation or anesthesia, to avoid any bias from various pretreatments, different scanner hardware or imaging regions or the need of repetitive anesthesia, the number of included patients is consistent. Thereby, the study provides proof-of-concept data to guide future larger prospective multicenter studies by identifying dw-MRI as potential predictive tool for treatment response in VM patients undergoing sclerotherapy.Second, two different sclerotic agents were used for sclerotherapy, which, however, is frequently performed in percutaneous sclerotherapy therapy to take advantage of certain properties of the respective agents ,4. ImporIn conclusion, the presented study shows, as proof-of-concept, that diffusion-weighted MRI has the potential to predict therapy response after percutaneous sclerotherapy of venous malformations. Once confirmed in larger studies, the identified radiomic features may help to guide therapeutic decisions based on the most important outcome—the improvement of patients’ quality-of-life.


Schistosoma spp. are unique among trematodes. Only females mating with male schistosomes can produce the highly immunogenic parasite eggs which determine the clinical picture of the disease schistosomiasis. The strong immune-modulatory effect of the eggs masks the influence of the adult worms. To shed light on the complexity of the immune response triggered by adult worms of Schistosoma mansoni, we performed a long-term unisexual infection experiment in mice. We were able to demonstrate that both male and female schistosomes can survive unpaired for one year in the murine host. Furthermore, unisexual S. mansoni infection leads to pronounced inflammation of the liver characterized by a non-polarized Th1/Th2 immune response, regardless of worm sex.In exhibiting gonochorism and phenotypic sexual dimorphism,  Schistosoma (S.) spp., which is endemic in approximately 78 countries, predominantly in the tropics and subtropics . PZQ kills the adult worms in the host but unfortunately does not protect against infection. Furthermore, large-scale deworming efforts in endemic areas could promote the emergence of PZQ-resistant strains  . Schistobtropics . The thr strains .+ T cells come into contact with egg antigens, cytokines  are released which cause eosinophils and endothelial cells to become activated. Proteomic analyses of egg excretory/secretory products have shown that highly immunogenic proteins are secreted abundantly. These include IPSE  and a ribonuclease omega-1. IPSE and omega-1 have been shown to promote Th2 differentiation directly  life cycle was maintained using Biomphalaria glabrata (B. glabrata) freshwater snails as intermediate hosts and 6- to 8-week-old female NMRI mice as definitive hosts, as previously described . Mice were sacrificed by cervical dislocation 52 weeks after infection under isoflurane anesthesia.The escribed . To obtaescribed . The fol® DxC 800 Synchron® Clinical System (Beckman Coulter GmbH). For histological evaluation, half of the right liver lobe was fixed in 4% neutral buffered formalin solution  and embedded in paraffin. Thin sections of 5 µm were stained with either hematoxylin/eosin (H&E) or Sirius Red (SR). Liver tissue sections were investigated histopathologically by an expert under blinded conditions, with particular attention paid to inflammatory infiltration, hepatocyte damage, bile duct deformation, parasite sections and fibrotic and architectural changes in liver structure. The severity of lesions was graded according to a modified Ishak score as minimal (one foci or less per 10x objective), mild (two to four foci per 10x objective), moderate (five to ten foci per 10x objective), or severe (more than 10 foci per 10x objective) , aspartate aminotransferase (AST) and alkaline phosphatase (AP) was performed using UniCeljective) . In thisjective) . The totIL-1β Mm00434228, IL-4 Mm00445259, IL-6 Mm00446190, IL-10 Mm01288386, IL-12α Mm00434169, IL-13 Mm00434204, IFN-γ Mm01168134, Acta-2 Mm00725412, Col1-α-2 Mm00483888 . Cycling was performed using QuantStudio 3 under the following reaction conditions: 50°C for 2 min followed by 95°C for 10 min, 45 cycles at 95°C for 15 s, and at 60°C for 1 min. Gene expression values were normalized to the endogenous reference gene gapdh  and presented as normalized expression values relative to naive controls.At 52 weeks post-infection, total RNA was isolated from snap frozen liver samples  and reversely transcribed into cDNA using High-Capacity cDNA Reverse Transcriptase Kit  according to the manufacturer’s instructions. RT-PCR was performed using the following TaqMan Gene Expression Assays: Single-cell suspensions were prepared by passing the spleen through a cell strainer (100 μm). This was followed by phosphate buffered saline  washing and erythrocyte lysis with RBC lysis buffer . Cells were washed twice with PBS and cell numbers were quantified using a CASY TT cell counter (OLS-Omni Life Science).S. mansoni soluble worm antigen preparation (SWAP) produced in-house. The concentrations of cytokines in the cell-free supernatants were determined using DuoSet ELISA kits  for the detection of IFN-γ, IL-4, IL-13 or IL-10 according to the manufacturer’s instructions.To determine cytokine production, isolated splenocytes were cultured in in RPMI 1640 medium supplemented with 10% FCS, 25mM HEPES and antibiotics, and stimulated for 72 hours at 37°C with a 10 µg/ml Animal experiments were performed in strict accordance with the regulations of the German Society for Laboratory Animal Science and with the European health guidelines issued by the Federation of Laboratory Animal Science Associations. The protocol was approved by the local committee on animal care and use (7221.3-1.1-036/18-1). Full efforts were made to minimize animal suffering.post hoc test. For all statistical analyses, p values < 0.05 were considered significant. *p < 0.05, **p < 0.01, ***p < 0.001.Statistical analysis was performed using GraphPad Prism 5.0 . Values are expressed as mean + SEM. Differences between groups were analyzed using the Kruskal-Wallis test followed by a Dunn’s S. mansoni infection on the final host organism, pathological organ changes were examined. Macroscopically, the livers of unisexually infected mice appeared dark brown and dull with a smooth surface  unisexual Additional analyses were performed on the liver enzymes aspartate aminotransferase (AST), alanine aminotransferase (ALT) and alkaline phosphatase (AP) as parameters for hepatic inflammation. AST, ALT and AP were significantly increased in the male-infected group compared with naive mice. In the female-infected group, liver enzymes also tended to be increased compared with naive mice   also tended to be increased in these groups -stimulated spleen cells. The increase was significant in the female-infected group compared to naive mice. IL-10 was significantly increased in the male-infected group and slightly increased in the female-infected group. The Th2 cytokines Il-4 and Il-13 were also found in the supernatants of both the male-infected and the female-infected groups stimulated with SWAP. IL-4 was significantly increased in the male-infected group and IL-13 was significantly increased in the female-infected group Figure 4S. mansoni in a mouse model, focusing on the predominant immune milieu of the host and the pathology of liver and spleen. We were able to show that long-term unisexual infection with S. mansoni leads to significant inflammation of the liver and tissue damage characterized associated with a non-polarized Th1/Th2 response.The aim of this study was to investigate the effects of a long-term (52 week) unisexual infection with In the present study, serum parameters showed increased AST and ALT levels, indicating hepatocyte damage . This waIn natural infection, oviposition by paired schistosomes in mice starts around 4 to 6 weeks after infection. Since hepatic inflammation is confined to perioval granulomas, the liver parenchyma is mostly unaffected and intact. In the absence of oviposition, liver inflammation occurs in the form of mild focal inflammation, focal lytic necrosis, apoptosis, and portal inflammation to the point of periportal or periseptal interface hepatitis. Upon preparation of the two infected groups, high numbers of live worms were found in the portal vein and the intrahepatic blood vessels, with the male schistosomes more likely to be found in the portal vein and the females deeper in the liver. In this context, it must be taken into account that the maturation of male and female schistosomes depends on different factors. The maturation of male schistosomes progresses independently of females , 31 and Schistosoma mansoni cercariae  arrives to mate with them. This assumption is supported by another study , in whicIn summary, unisexual schistosomes survive in mice for at least one year. They cause visible and measurable hepatitis during infection associated with a non-polarized Th1/Th2 response. However, the immature stage of development of the female worms as a comparison group to the mature adult worms must be considered here. The extent to which unpaired worms would still be able to mate in the presence of a suitable partner after a year is uncertain. Also, the question arises as to whether and how an emerging immunomodulatory effect brought about by parasite eggs would affect the host this long after the onset of unisexual infection.The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.The animal study was reviewed and approved by local committee on animal care and use (7221.3-1.1-036/18-1).Conceptualization, MS, CR, ER. Formal analysis, MS, CR, NK, FW. Investigation, MS, CR, FW, AR, NK. Data maintenance, MS and CR. Writing - preparation of first draft, MS and CR. Writing - review and editing, MS, FW, ER. Visualization, MS. Supervision, MS, ER. All authors contributed to the article and approved the submitted version.The skillful technical support of Daniel Wolter and Mohamed Elhensheri  is gratefully acknowledged. The work was funded by the European Social Fund project Card-ii-omics (ESF/14-BM-A55-0037/16).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.